Multi-Criteria Decision Making Methods for Designing Optomechatronic Systems

Article Preview

Abstract:

When designing unique optomechatronic systems with the application of innovative solutions, decision making with respect to a number of technical and economic criteria seems to be an essential problem. The multi-criteria decision theory is a process of selecting the best solution to the set of alternatives. The paper presents the application of the TOPSIS method for working towards a solution to decision making in the process of designing a unique measurement vision system. The set of alternatives for the vision system has been considered with regard to benefit and cost criteria. As a result, the best alternative has been identified, which represents the highest similarity to the ideal solution expressed by the value of the relative closeness index.

You might also be interested in these eBooks

Info:

Periodical:

Solid State Phenomena (Volumes 220-221)

Pages:

188-193

Citation:

Online since:

January 2015

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] H. Cho, Optomechatronic: Fusion of Optical and Mechatronic Engineering, CRC Press Taylor&Francis Group, (2006).

Google Scholar

[2] H. Hosaka, Y. Katagiri, T. Hirota, K. Itao, Optomechatronics, Marcel Dekker, Inc., (2005).

Google Scholar

[3] T. J. van Beek, M. Erden, T. Tomiyama, Modular design of mechatronic systems with function modelling, Mechatronics 20 (2010) 850–863.

DOI: 10.1016/j.mechatronics.2010.02.002

Google Scholar

[4] T. R. Browning, Applying the design structure matrix to system decomposition and integration problems: a review and new directions, IEEE Transactions on Engineering Management 48(3) (2001) 292–306.

DOI: 10.1109/17.946528

Google Scholar

[5] E. P. Hong, G. J. Park, Modular Design Method Using the Independence Axiom and Design Structure Matrix in the Conceptual and Detailed Design Stage, Daejeon, ICAD, 2011, p.134–141.

Google Scholar

[6] H. Komoto, T. Tomiyama, Multi-disciplinary system decomposition of complex mechatronics systems, CIRP Annals – Manufacturing Technology 60 (2011) 191–194.

DOI: 10.1016/j.cirp.2011.03.102

Google Scholar

[7] G. Pahl, W. Beitz, J. Feldhusen, K.H. Grote, Engineering Design, London Springer-Verlag, (2007).

Google Scholar

[8] V. M. Athawale, S. Chakraborty, A TOPSIS Method-based Approach to Machine Tool Selection, Dhaka, IIEOM, (2010).

Google Scholar

[9] C. P. Kiran, S. Clement, V. P. Agrawal, Coding, evaluation and optimal selection of a mechatronic system, Expert Systems with Applications 38 (2011) 9704–9712.

DOI: 10.1016/j.eswa.2011.01.171

Google Scholar

[10] T. Yang, Ch-Ch. Hung, Multiple-attribute decision making methods for plant layout design problem, Robotics and Computer-Integrated Manufacturing 23 (2007) 126–137.

DOI: 10.1016/j.rcim.2005.12.002

Google Scholar

[11] M. Behzadian, S. K. Otaghsara, M. Yazdani, J. Ignatius, A state-of the-art survey of TOPSIS applications, Expert Systems with Applications (39) (2012) 13051–13069.

DOI: 10.1016/j.eswa.2012.05.056

Google Scholar

[12] J. Montusiewicz, Wspomaganie procesów projektowania i planowania wytwarzania w budowie i eksploatacji maszyn metodami analizy wielokryterialnej, Politechnika Lubelska, Lublin, (2012).

Google Scholar

[13] C. L. Hwang, K. Yoon, Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, New York, (1981).

Google Scholar

[14] T. L. Saaty, Decision making with the analytic hierarchy process, Int. J. Services Sciences 1(1) (2008) 83–98.

Google Scholar

[15] T. Giesko, Dual-camera vision system for fatigue monitoring, Materials Science Forum; 726 (2012) 226–232.

DOI: 10.4028/www.scientific.net/msf.726.226

Google Scholar